On account of its suitability for in-situ and on-line chemical analysis, Raman spectroscopy is increasingly being used in industrial process engineering and environmental metrology, wherein a disadvantage includes the fact that in practice the fluorescence and/or the scattering properties of some samples result in the generation of spectra whose quality is affected by a high background, particularly if the samples are not prepared and compact equipment is used.
One approach to solving this problem is the technique of shifted-excitation Raman difference spectroscopy (also referred to as “SERDS” in the following), wherein two Raman spectra whose excitation wavelengths are slightly shifted with respect to each other are recorded. The broadband background is eliminated by subtraction, and the Raman spectrum is reconstructed from the difference spectrum.
Tuning the excitation wavelength by means of the temperature has been a usual method since diode lasers were made available, wherein the temperature is typically controlled and stabilized thermoelectrically. The change in temperature enables the emission wavelength to be shifted by some nanometers (J. Zhao, M. M. Carraba, and F. S. Allen, Appl. Spectrosc. 56, 834 (2002)).
However, the wavelength stability of simple Fabry-Perot diode lasers is not sufficient for performing Raman spectroscopy so that additional stabilization is necessary therefor. For example, external-cavity semiconductor lasers (ECL lasers) enable the frequency to be shifted by turning the outer grating (T. F. Cooney, H. T. Skinner and S. M. Angel in Appl. Spectrosc., Vol. 49 (1995), pp 1846-1851).
If no tunable laser source is available, the majority of dispersive spectrometers provide the possibility of turning the grating by a small angle, whereby the spectrum spectrally shifts together with the background by the amount Δ (Steven E. J. Bell, Elsa S. O. Bourguignon and Andrew Dennis, Analyst, Vol. 123 (1729-1734) (1998)).
From WO 2006/134103 A1 and M. Maiwald, G. Erbert, A. Klehr, H. -D. Kronfeldt, H. Schmidt, B. Sumpf and G. Tränkle, Appl. Phys. B 85, 509-512 (2006) it is known to directly modulate the wavelength of a DFB laser by means of the injection current of the DFB laser. Being driven at 785 nm at two different amperages causes the frequency-stable DFB diode laser to accordingly emit at two different wavelengths. The main advantage includes the possibility of quickly switching between two wavelengths, wherein no movable parts are required. Thus, this method is cut out for fast on-line chemical analysis.
WO 2006/130728 A2 discloses a method for generating and detecting a Raman spectrum of a medium to be analyzed, wherein a difference spectrum is calculated by subtraction of the first spectrum and the second spectrum.
Various algorithms for reconstructing a Raman spectrum from a difference spectrum are known in the prior art.
Shreve et al. (R. A. Mathies, A. P. Shreve, N. J. Cherepy, Appl. Spectrosc. 46, 707 (1992)) describe a manual fit of Lorentz functions to the difference spectrum according to the method of least error squares. However, this modeling requires previous knowledge of the original spectrum as well as a check by a user, which is why this technique cannot be automated.
Since SERD spectra are similar to first-order derivative spectra, integration thereof is obvious. This process can be automated but results in the formation of artifacts so that manual finishing work is necessary.
Matousek et al. describe a linear recursive algorithm with linear interpolation between the data points (P. Matousek, M. Towrie, and A. W. Parker, “Simple reconstruction algorithm for shifted excitation Raman difference spectroscopy,” Applied Spectroscopy, vol. 59, 2006). This algorithm can be automated, but there are preconditions for the distribution of the difference signals in the SERD spectra so that this method is not universally applicable. Moreover, this method results in the formation of artifacts, too.
Zhao et al. describe several integral transformations for the reconstruction of spectra, said transformations being based on the deconvolution of the SERD spectrum (J. Zhao, M. Carrabba, and F. Allen, Applied Spectroscopy, vol. 56, no. 7, 2002). These transformations can be automated, but the resulting reconstruction spectra are not free from artifacts, either.
Rebecca Willett describes the reconstruction problem as an inverse Poisson problem and uses a statistical expectation-maximization algorithm (Multiscale reconstruction for photon-limited shifted excitation Raman spectroscopy,” ICASSP 2007). However, the used algorithm is not fully formulated, and there are some unanswered questions with respect to experimental realization regarding the selection of and the number of excitation frequencies.
The known algorithms for spectrum reconstruction provide purely qualitative spectra, and they result in the formation of artifacts or require previous knowledge of the Raman spectrum or preconditions for the SERD spectra so that automated and, at the same time, qualitative and quantitative SERD spectroscopy (e.g., concentration measurement series) is not possible according to the prior art.
It is therefore the object of the present invention to provide a method and a device for generating and for detecting a Raman spectrum that enable automated or automatable and, at the same time, qualitative and quantitative SERD spectroscopy (e.g., concentration measurement series).